Skin and Bones: The Contribution of Skin Tone and Facial
Structure to Racial Prototypicality Ratings
Michael A. Strom1, Leslie A. Zebrowitz1*, Shunan Zhang1, P. Matthew Bronstad1, Hoon Koo Lee2
1 Department of Psychology, Brandeis University, Waltham, Massachusetts, United States of America, 2 Department of Psychology, Yonsei University, Seoul, Korea
Abstract
Previous research reveals that a more ‘African’ appearance has significant social consequences, yielding more negative first
impressions and harsher criminal sentencing of Black or White individuals. This study is the first to systematically assess the
relative contribution of skin tone and facial metrics to White, Black, and Korean perceivers’ ratings of the racial
prototypicality of faces from the same three groups. Our results revealed that the relative contribution of metrics and skin
tone depended on both perceiver race and face race. White perceivers’ racial prototypicality ratings were less responsive to
variations in skin tone than were Black or Korean perceivers’ ratings. White perceivers ratings’ also were more responsive to
facial metrics than to skin tone, while the reverse was true for Black perceivers. Additionally, across all perceiver groups, skin
tone had a more consistent impact than metrics on racial prototypicality ratings of White faces, with the reverse for Korean
faces. For Black faces, the relative impact varied with perceiver race: skin tone had a more consistent impact than metrics for
Black and Korean perceivers, with the reverse for White perceivers. These results have significant implications for predicting
who will experience racial prototypicality biases and from whom.
Citation: Strom MA, Zebrowitz LA, Zhang S, Bronstad PM, Lee HK (2012) Skin and Bones: The Contribution of Skin Tone and Facial Structure to Racial
Prototypicality Ratings. PLoS ONE 7(7): e41193. doi:10.1371/journal.pone.0041193
Editor: Galit Yovel, Tel Aviv University, Israel
Received January 21, 2012; Accepted June 18, 2012; Published July 18, 2012
Copyright: ß 2012 Strom et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by NIH Grants MH066836 and K02MH72603 to the first author (http://www.nimh.nih.gov/). The funders had no role in study
design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: zebrowitz@brandeis.edu
color emerged as the most important cue [6]. Consistent with
people’s ratings of the importance of skin tone, both Black and
White perceivers categorize Black individuals according to their
skin tone, as evidenced in an implicit recall measure of who said
what when targets differed in skin tone, which paralleled the effects
found when targets differed in race [7]. Using a similar paradigm,
African-American children showed better memory of what story
characters did when the stories paired light-skinned Black targets
with positive traits and high status occupations and dark-skinned
Black targets with negative traits and low status occupations [8].
Also, both Black and White perceivers reported more negative
cultural beliefs about the traits of darker-skinned than lighterskinned Black targets, with the reverse trend for positive beliefs [7].
Another study found that European Americans high in racial
prejudice were faster to recognize the onset of anger and slower to
recognize the offset of anger in schematic Black than White faces,
when face race was manipulated solely by skin tone [9]. Although
the foregoing studies did not assess perceived racial prototypicality
per se, they do provide reason to believe that skin tone may be an
important determinant of such judgments. Also, while the
foregoing studies assessed Black and/or White perceivers responses to skin tone, there is evidence for a preference for light skin in
Asian perceivers as well [10], suggesting that skin tone may be an
important determinant of perceived racial prototypicality for
Koreans as well as for Black and White Americans.
Although the results of the foregoing studies may reflect
responses to skin tone, it is also possible that many reflect
responses to facial structure. For example, the images conjured up
when participants were instructed to think of darker- vs. lighter-
Introduction
Recent research provides strong evidence that responses to faces
are influenced not only by their perceived racial category, but also
by their phenotypic qualities regardless of category. Black or
White individuals who are judged to have a more prototypically
Black appearance elicit more stereotyped trait impressions [1],
more negative associations [2], and harsher penalties in the
criminal justice system [3,4]. Indeed racial prototypicality
sometimes has a stronger effect on social outcomes than racial
category, perhaps because people try to avoid race bias but are
unaware of the more subtle prototypicality bias [5]. Whereas
significant effects of racial prototypicality have been welldocumented, the question remains as to what facial qualities
influence perceived racial prototypicality. The goal of the present
research was to investigate the relative influence of skin tone and
facial metrics on racial prototypicality ratings of White, Black, and
Korean perceivers, and whether these effects vary with face race.
Although we recognize that anthropologists and biologists question
the validity of race as a scientific concept (e.g., Lewontin 1972), it
is nevertheless, a widely accepted concept in folk psychology
(Zuckerman 1990). While acknowledging that clear decisions on
category membership are problematic, we use the ‘fuzzy’ category
system of racial groups and the terms White, Black, and Korean to
denote the physical appearance of target faces and the group
identification of perceivers in this research.
Much of the research investigating the facial qualities involved
in race perception has emphasized variations in skin tone. When
simply asking participants to rate the importance of various facial
features and skin color in determining the race of a target, skin
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Skin Tone, Face Structure, Race Prototypicality
informed prediction about this effect, since the literature has
largely confounded perceiver and face race, focusing on White
perceivers’ responses to Black faces, with only one study examining
Asian perceivers’ responses to Asian and White faces. Achieving
these two aims not only will inform our understanding of face
perception, but it also has practical importance. As noted above,
more African-looking White or Black defendants receive longer
prison sentences [3], and more African-looking Black defendants
convicted of murdering a White victim are more likely to receive
the death penalty [4]. Our results will have significant implications
for predicting who will experience racial prototypicality biases and
from whom.
skinned Black targets [7] may have differed on dimensions other
than skin tone. Other research that has separated effects of skin
tone and facial structure suggests that facial structure may be more
important. A neuroimaging study found that regardless of whether
Black faces had light or dark skin, they elicited higher amygdala
activation (an indicator of emotional salience) in White viewers
than did White faces, suggesting the importance of facial structure
[11]. Similarly, other researchers found that observers’ evaluations
of a perpetrator in a simulated news report did not differ whether
given light, medium, or dark skin when facial structure was held
constant [12]. In a more recent investigation, ratings of skin tone
and racial prototypicality of grey scale facial images were collected
using the lightness contrast illusion [13]. As predicted, when a grey
scale image of a face that had been morphed to a mixed Black and
White racial appearance was surrounded with Black faces, color
ratings of the face were lighter than when it was surrounded with
White faces. However, the face’s perceived racial prototypicality
was not affected, suggesting that facial metrics may be the more
influential cue to racial prototypicality. In contrast to the foregoing
failures to find independent effects of skin tone on judgments of
Black faces or Black-White morphs, another study found
independent effects of both skin tone and face shape on racial
categorization of Japanese and White faces [14].
The preceding research has several limitations. First, previous
research has not systematically investigated effects of perceiver
race on the relative influence of skin tone and facial structure. In
many studies perceiver race is not reported, and in those that do
report race, the large majority of participants were White, thereby
precluding analyses to examine effects of perceiver race. Yet, there
is reason to predict such effects. Anecdotal evidence regarding
differential treatment of darker and lighter skinned Blacks within
the African-American community [10] coupled with an injunction
to be ‘color blind’ that is experienced by White Americans, but
possibly not Koreans, suggests that racial prototypicality ratings of
White perceivers may be less responsive to skin tone than those of
Black or Korean perceivers. Indeed, this prediction is consistent
with the research summarized above that used perceivers whose
race was either unspecified or predominantly White [11–13] and
found that facial structure trumped skin tone. In contrast, the one
study of Japanese perceivers found an influence of both [14]. An
additional limitation of the existing research is that it has not
systematically investigated moderating effects of face race on the
relative influence of skin tone and facial structure. However, it is
noteworthy that the studies that found that facial structure was
more important than skin tone examined faces that were
completely or partially Black, whereas one that found that the
two were equally important examined faces that were White or
Japanese. A final limitation of the existing research vis a vis the
aims of the present study is that many of the studies bear on
processes other than racial prototypicality ratings.
The present study filled the aforementioned gaps in our
understanding of racial prototypicality by achieving two aims.
The first was to compare the relative contribution of skin tone and
facial metrics to the racial prototypicality ratings of White, Black,
and Korean perceivers. Based on the existing research we
predicted that White perceivers would be more influenced by
facial metrics than skin tone [11–13], whereas the two facial
qualities would have relatively equal influence for Korean
perceivers [14] and that Black perceivers may be more influenced
by skin tone [10]. We further expected that White perceivers
would be less influenced by skin tone than perceivers of other
races. Our second aim was to determine whether the relative
contributions of skin tone and facial metrics to racial prototypicality judgments differ across face race. It is difficult to make an
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Methods
Ethics Statement
The research was conducted in accordance with the ethical
principles for research involving human subjects expressed in the
Declaration of Helsinki. The research protocol was approved by
the Institutional Review Board at Brandeis University. Written
informed consent was obtained from all participants.
Participants
Thirty nine White American college undergraduates (17 males),
26 Black American college undergraduates (11 males), and 48
Korean college undergraduates (24 males) at a university in Seoul,
Korea rated race-related appearance qualities and emotion
expression of the target faces. White and Korean participants
were randomly assigned to rate either male or female faces, while
Black participants rated faces of both sexes with the order of face
sex counterbalanced across participants. Thus, each face was rated
by approximately 20 White participants, 26 Black participants,
and 24 Korean participants. White participants received either
$10 or course credit for their participation in a single session, and
Korean raters received the equivalent of $10 in their local
currency for participation in a single session. Black participants
received $25 for their participation in two experimental sessions.
Faces
There were 60 White facial images, 60 Black facial images, and
60 Korean facial images, with male and female faces equally
represented, all of which had been used in a previous study [15].
Four criteria were used for target face selection: neutral
expression, no head tilt, no glasses, and no facial hair. Faces were
presented in color against a beige background. White facial images
were selected from a variety of databases: University of Stirling
PICS database, the AR face database [16], and yearbooks from an
American high school and a university. The facial images of Black
males were from a set of faces that had been used in a study that
found significant effects of racial prototypicality on stereotyping
[1]. These images had been selected by the authors from
American high school yearbooks. The images of the Black female
target faces were selected from the website http://americansingles.
com by searching for Black females ages 18–25. Korean facial
images were selected randomly from a Korean university yearbook
with the constraint that they meet the four selection criteria listed
above.
Facial Metric Measurements
Following the procedure in previous studies [17,18,19], in house
software was used to mark 64 points on digitized images of each
face viewed on a 21 inch PC monitor, from which facial metrics,
normalized by interpupil distance, were computed using automatic
procedures written in Visual Basic and Excel. This is a standard
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Skin Tone, Face Structure, Race Prototypicality
normalization technique to control for variations in distance from
the camera [20–22]. Points marked by two research assistants
(Figure 1, Panel A) yielded 21 facial metrics with acceptable interjudge reliability (rs .7 for faces of all races and both genders), and
these were used in subsequent analyses (Figure 1, Panel B).
Evidence for the predictive validity of facial metrics derived
through this procedure has been provided in previous research
that input the metrics into connectionist models. For example,
adult faces with metrics that resemble those of babies were rated as
more babyfaced and as possessing more childlike traits [17];
normal faces with metrics that resemble those of anomalous faces
were rated as less attractive and less healthy [17]; neutral
expression White, Black, and Korean faces with metrics that
resemble those of angry expression faces were rated as more
hostile and less trustworthy [19].
Other Appearance Ratings
Three control appearance variables (attractiveness, babyfaceness, and smiling) were taken from ratings of the faces provided by
the same participants for a previous study in which these ratings
had shown acceptable reliability [15]. Although all faces were
selected to have a neutral expression, a smile variable was created
by dividing the number of times participants had identified the
face as happy by the total number of participants (other
expressions were not mentioned with sufficient frequency to
create additional control variables). Attractiveness (unattractive –
attractive) and babyfaceness (babyfaced – maturefaced) were rated
on 7-point scales. Faces also were rated as to how masculine/
feminine they looked, but these ratings were not used in the
analyses.
Korean Translation
Skin Tone Ratings
All rating scales were translated into Korean by a native Korean
speaker. A second native Korean speaker translated the Korean
back into English, and these results were compared to the original
English-language scales. For any discrepancies, the native Korean
speakers were consulted to retranslate the scales so that the
meaning in Korean was as close as possible to the meaning in
English.
All faces were rated on a 7-point scale assessing skin tone (very
light skin color – very dark skin color). We used a subjective rating
of skin tone rather than objective measures because, for our
purposes, the contribution to prototypicality judgments of perceived
differences in skin tone among faces that are all the same race is
the most relevant variable. The standardized alpha for skin tone
ratings was.92, averaged across ratings of male and female faces of
each race by perceivers of each race.
Procedure
Perceivers viewed images and input responses on Pentium 4
personal computers with Windows XP and 19’’ CRT displays with
128061024 screen resolution. Raters sat within 36’’ of the
monitors. MediaLab 2004.2.1 [23] was used to display images
and collect ratings. Identical computers and monitors were
purchased for data collection in Korea, and identical Medialab
programs for presentation of stimuli with English or Korean
instructions and rating scales were prepared in the Brandeis face
perception lab. Faces were displayed until a rating was made, with
a maximum duration of 5 seconds, after which the face
disappeared and the rating scale remained until a rating was
made. Faces of each race were rated first on prototypicality
Racial Prototypicality Ratings
All faces were rated on 7-point appearance scales assessing:
Caucasian appearance (not at all Caucasian/White – very Caucasian/
White), African appearance (not at all African – very African), and
Asian appearance (not at all Asian - very Asian). Standardized alphas
averaged across ratings of male and female faces of each race by
perceivers of each race were.83 for Caucasian appearance
ratings,.85 for African appearance ratings, and 86 for Asian
appearance ratings.
Figure 1. Facial metric measurements. Panel A shows location of points utilized for establishing facial metrics. When identical points were
marked on the right and left side, only those on the person’s right side are indicated. Panel B shows location of the reliably measured facial metrics
that were used in the discriminant function analysis. Panel C shows location of facial metrics that significantly discriminated different race faces and
were used in the regression analyses.
doi:10.1371/journal.pone.0041193.g001
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Skin Tone, Face Structure, Race Prototypicality
p,001, reflecting a tendency for Black faces to be rated as darker
skinned than both White and Korean faces, ps ,001, and for
Korean faces to be rated as darker than White faces, p,001. A
significant effect of rater race, F (2, 177) = 18.83, p,001, reflected
a tendency for both White and Korean perceivers to give darker
skin tone ratings than did Black perceivers, ps = 001. There also
was a significant rater race by face race interaction, F (4,
177) = 10.44, p,001. Planned comparisons revealed that the
overall tendency to rate Black faces as darker than Korean faces
which in turn were rated as darker than White faces was significant
for perceivers of all races with the exception of White perceivers
ratings of White and Korean faces, p = .15 (see Table 2).
pertinent to that race (e.g. Black faces were rated first on African
prototypicality), with the order of the other two prototypicality
judgments counterbalanced. Perceivers were instructed to focus on
rating each face according to how racially prototypical the features
were. Although participants were instructed to focus on how
racially prototypical the features were, the finding that perceived
skin tone predicted those ratings over and above facial metrics
indicates that they captured racial prototypicality more broadly.
The order in which Black, White, and Korean faces were rated
was counterbalanced across raters.
Results
Discriminating Facial Metrics and Perceived Skin Tone
Effects of Skin Tone vs. Facial Metrics on Perceived Racial
Prototypicality
To select a set of facial metrics most likely to influence
prototypicality ratings, we entered the 21 reliable facial metrics
simultaneously into discriminant function analyses comparing two
races at a time to identify metrics that objectively discriminated
between faces of different races. The discriminant analyses were
statistically significant for each of the racial comparisons: White
and Black faces’ Wilks’ Lambda = 24, Chi-square = 162.92,
p,001; White and Korean faces’ Wilks’ Lambda = 18, Chisquare = 197.64, p,001; and Black and Korean faces’ Wilks’
Lambda = 10, Chi-square = 262.36, p,001. A total of eleven
facial metrics objectively discriminated at least two groups of faces
(Figure 1, Panel C). The standardized coefficients for each metric
are shown in Table 1. The means and standard deviations of the
facial metrics that objectively discriminated the races as well as the
skin tone ratings are shown in Table 2. Compared to Black faces,
White faces had wider jaws, narrower noses, thinner lips, lower
eyebrows, and longer chin to pupil height. Compared to Korean
faces, White faces had larger vertical eye height (distance from the
upper to lower eyelid), smaller jaw width, smaller eye separation,
smaller eyebrow separation, wider mouths, thinner lips, and lower
eyebrows. Compared to Korean faces, Black faces had narrower
jaws, smaller eye separation, wider and shorter noses, smaller
eyebrow separation, larger horizontal eye width, and larger mouth
width.
A 3 (face race) 6 3 (rater race) analysis of variance on skin tone
ratings revealed a significant effect of face race, F (2, 177) = 39.98,
Table 3 shows the mean racial prototypicality ratings of White,
Black, and Korean faces by raters of each race. Not surprisingly,
perceivers of all races rated White faces as higher in Caucasianthan African- or Asian-prototypicality, Black faces as higher in
African- than Caucasian-or Asian-prototypicality, and Korean
faces as higher in Asian- than Caucasian- or African- prototoypicality. Also, Caucasian prototypicality ratings were higher for
White than Black or Korean faces, African ratings were higher for
Black than White or Korean faces, and Asian ratings were higher
for Korean than White or Black faces.
To examine facial qualities than influenced the perceived racial
prototypicality of faces within each race, we performed a series of
regression analyses predicting racial prototypicality ratings using
face as the unit of analysis, which was justified by high inter-rater
reliabilities for the face ratings, as described above. Specifically, for
faces of each race, we predicted mean racial prototypicality ratings
(Caucasian-appearance, African-appearance, and Asian-appearance) by White, Black, or Korean perceivers from their mean skin
tone ratings and the facial metrics that had discriminated any of
the racial groups, controlling face sex, attractiveness, babyfaceness,
and smile ratings. The control variables were entered at Step 1. To
determine the unique variance accounted for by skin tone, facial
metrics were entered at Step 2, and perceived skin tone was
entered at Step 3. To determine the unique variance accounted for
Table 1. Objectively Discriminating Facial Metrics.
Metric Label
Metric Name
E5
Vertical Eye height
Standardized Coefficients with t-values (in parentheses)
White vs. Black Faces
W1
Jaw width
E1
Eye separation
N2
Nose width
N3
Nose length
B1
Eyebrow separation
E4
Horizontal eye width
M0
Mouth width
White vs. Korean Faces
Black vs. Korean Faces
.54 (7.07**)
.53 (4.36**)
2.53 (7.76**)
2.97 (11.03**)
2.49 (12.12**)
2.46 (13.13**)
2.85 (9.68**)
.67 (7.00**)
2.62 (7.02*)
2.38 (6.67**)
2.29 (4.46**)
.34 (2.09*)
.34 (5.97**)
.36 (9.06**)
M1
Lip thickness
2.57 (9.94**)
2.31 (5.54**)
B2
Eyebrow height
2.34 (3.03*)
2.23 (4.50**)
C1
Chin to pupil height
.49 (3.79**)
Note. Positive values for standardized coefficients indicate higher values for White faces, and for Black faces in the Black vs. Korean analysis.
*p,.05;
**p,001.
doi:10.1371/journal.pone.0041193.t001
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Table 2. Descriptives for Facial Quality Predictors.a
Facial Quality
Name
Face Race
Metric
Label
White
Black
M
SD
M
Korean
SD
M
SD
Vertical Eye height
E5
.17
.02
.16
.02
.14
.02
Jaw width
W1
1.87
.11
1.77
.14
2.03
.12
Eye separation
E1
.51
.03
.51
.03
.59
.03
Nose width
N2
.57
.05
.66
.06
.60
.04
Nose length
N3
.72
.07
.68
.06
.75
.05
Eyebrow separation
B1
.37
.10
.41
.11
.50
.11
Horizontal eye width
E4
.81
.05
.84
.05
.76
.05
Mouth width
M0
.84
.11
.88
.08
.80
.07
Lip thickness
M1
.25
.06
.34
.05
.30
.04
Eyebrow height
B2
.36
.05
.39
.05
.40
.04
Chin to pupil height
C1
1.84
.12
1.76
.13
1.87
.11
1.00
4.62b
1.35
3.43a
.90
b
1.54
3.64c
.96
.99
3.86c
1.06
Skin Tone
White Perceivers
3.14a
a
Black Perceivers
2.29
Korean Perceivers
3.24a
.83
4.21
1.20
4.42b
a
Note. Means for facial metrics that did not discriminate a particular race from the others are shown in italics. Skin tone means with different superscripts within each
perceiver group differ at p,01 or better.
doi:10.1371/journal.pone.0041193.t002
change in R2 for African prototypicality ratings of faces of all
races, all ps ,001.
Facial metrics did not produce a significant change in R2 for
White perceivers’ African prototypicality ratings of White faces,
p.05, but there was a significant change for their ratings of Black
faces, p,05, and Korean faces, p,001. A similar pattern was
shown for Black perceivers, with facial metrics producing a
significant change in R2 for African prototypicality ratings of Black
faces, p,001, and Korean faces, p,05, but not White faces, p.05.
For Korean perceivers, facial metrics produced a significant
change in R2 for African prototypicality ratings of Korean faces,
p,05, but not White or Black faces, ps .05.
Asian prototypicality ratings. Skin tone did not produce a
significant change in R2 for White perceivers’ ratings of White,
Black, or Korean faces, all ps .05, In contrast, skin tone produced
a significant change in R2 for Black and Korean perceivers ratings
of White and Black faces, ps ,001, but not Korean faces, p.05.
Facial metrics did not produce a significant change in R2 for
Asian prototypicality ratings of White or Black faces by perceivers
of any race, all ps .05, whereas the change in R2 was significant
for Asian prototypicality ratings of Korean faces for perceivers of
all races, all ps ,001.
by facial metrics, perceived skin tone was entered at Step 2 and
facial metrics were entered at Step 3. These regression analyses
were repeated for faces of each race rated by each of the three
groups of perceivers. Table 4 shows the changes in R2 associated
with the discriminating facial metrics and perceived skin tone
when each was entered at Step 3 of the regression analyses
predicting the three racial prototypicality ratings of White, Black,
and Korean faces by perceivers of each race.
We also performed exploratory analyses to determine the
particular facial metrics that influenced perceived racial prototypicality and whether these varied with face and perceiver race.
Because we had no a priori predictions for many of the metrics we
examined, the large number of metric - prototypicality relationships capitalizes on chance (3 face race 6 3 perceiver race 6 3
prototypicality ratings 6 10 discriminating metrics). We therefore
report these data in Supplementary Table S1 for the interested
reader rather than in the text.
Caucasian prototypicality ratings. Skin tone did not
produce a significant change in R2 for White perceivers’ ratings
of faces of any race, all ps .05. In contrast, skin tone produced a
significant change in R2 for Black and Korean perceivers ratings of
White faces and Black faces, and for Korean perceivers ratings of
Korean faces, all ps ,001.
Facial metrics produced a significant change in R2 for both
White and Black perceivers’ Caucasian prototypicality ratings of
White faces, both ps ,05, as well as Black and Korean faces, all ps
,001. Facial metrics did not produce a significant change in R2
for Korean perceivers’ ratings of White faces, p.05, whereas there
was a significant change for their ratings of Black faces, p,05, and
Korean faces, p,001.
African prototypicality ratings. Skin tone produced a
significant change in R2 for White perceivers’ ratings of White
faces, p,05, and Korean faces, p,001, but not Black faces, p.05.
For Black and Korean perceivers, skin tone produced a significant
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Discussion
Within race variations in racial prototypicality have been shown
to influence important social outcomes [1,4,5]. We add to this
literature by determining the relative contribution of skin tone and
facial metrics to variations in perceived racial prototypicality by
White, Black, and Korean pereceivers, information that is essential
to predicting who will experience racial prototypicality biases and
from whom. As predicted, the racial prototypicality ratings of
White perceivers were the least responsive to variations in skin
tone. Across the three prototypicality ratings made for faces of
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Skin Tone, Face Structure, Race Prototypicality
Table 3. Descriptives for Racial Prototypicality Ratings.a
Face Race
Perceiver
Race
Racial
Prototypicality
White
M
White
Black
Korean
Black
SD
Caucasian
5.02
a
African
2.19b
Asian
M
Korean
SD
.80
2.68
c
.43
4.99a
2.26b
.38
Caucasian
5.25a
African
M
SD
.74
3.12
d
.54
.75
1.76c
.30
2.78c
.83
5.56a
.52
.91
2.41b
.72
2.52b
.74
2.23b
.66
4.96a
.99
2.37b
.50
Asian
2.20b
.63
2.04c
.51
5.44a
.59
Caucasian
4.56a
.96
3.00b
1.01
3.10b
.80
African
2.98b
.80
5.00a
1.03
3.07b
.78
.78
b
a
.76
Asian
3.33
c
3.01
.86
4.82
a
Note. Within each perceiver race, face race effects (row means) with different superscripts and racial prototypicality effects (column means) with different subscripts
differ at p,05 or better.
doi:10.1371/journal.pone.0041193.t003
each of the three races, only 2 skin tone effects attained statistical
significance for White perceivers, as compared with 7 and 8
significant effects of skin tone for Black and Korean perceivers,
respectively. Moreover, White perceivers showed less responsiveness to skin tone than to facial metrics (2 significant effects for skin
tone vs. 6 significant effects for facial metrics), whereas Black
perceivers showed more responsiveness to skin tone than to
metrics (7 vs. 4 significant effects), and Korean perceivers showed
fairly high responsiveness to both skin tone and metrics (8 vs. 6
significant effects). In addition, the relative impact of skin tone and
facial metrics on racial prototypicality ratings varied with face
race. For White faces, skin tone had a more consistent effect than
facial metrics (7 significant effects for skin tone vs. 2 significant
effects for facial metrics). For Korean faces, skin tone had a less
consistent effect than metrics (4 vs. 9 significant effects). In the case
of Black faces, the relative influence of skin tone and metrics was
fairly equal (6 vs. 5 significant effects), but the pattern varied across
perceiver race. For both Black and Korean perceivers, the skin
tone effects on all three racial prototypicality ratings were
significant, whereas none was significant for White perceivers. In
contrast, facial metrics had significant effects on 2 out of 3 racial
prototypicality ratings of Black faces for White and Black
perceivers, as compared with none for Koreans.
The finding that White perceivers’ racial prototypicality ratings
were less responsive to skin tone than to facial metrics is a striking
effect given that skin tone and racial prototypicality ratings were
both rated by perceivers, whereas facial metrics were objectively
assessed. This ascendance of facial metrics is consistent with
previous research that studied White perceivers and found that
facial metrics trumped skin tone when assessing neural indicators
of the emotional salience of faces [11], evaluations of criminals in
simulated news reports [12], and prototypicality ratings of racially
ambiguous morphs [13]. The finding that White perceivers’ racial
prototypicality ratings were less responsive to skin tone than were
ratings by Black or Korean perceivers is consistent with the
cultural injunction to be ‘color blind,’ suggesting that White
Americans may ignore skin tone variations so as not be perceived
as racist. Although one could argue that perceivers should also
strive to be ‘racial feature blind,’ research indicates that people are
largely unaware of the influence of these subtle features, and are
also unable to monitor their use, even when instructed to do so [5].
PLoS ONE | www.plosone.org
In addition to a possible contribution of culturally variable
political correctness to the moderating effects of perceiver race,
variations in perceptual experience may also make a contribution.
Indeed, Black perceivers ratings of the skin tone of Black faces
showed the highest variability (Table 2), suggesting that skin tone
may have had stronger effects on prototypicality ratings by Black
than White Americans because the former are culturally sensitized
to subtle variations in skin tone [10]. However, Korean perceivers
did not show more variability in skin tone ratings than White
Americans even though their prototypicality ratings did show
stronger effects of skin tone. Whatever the explanation for
variations across perceiver race, the present findings provide an
important qualification to the Brooks and Gwinn conclusion that
facial feature variations have a greater effect than skin tone on
perceived racial prototypicality [13]. While our data support that
claim for White perceivers, they do not support it for others, and
the failure to find effects of skin color manipulations in previous
research may reflect the focus on White perceivers.
Some limitations to the predictors of racial prototypicality that
we have documented should be noted. One is that the facial
metrics we assessed were not exhaustive. Neither was our measure
of skin tone, and it might be interesting for future research to see
whether other qualities, such as hue, pigmentation, and contrast
affect prototypicality ratings since they have been found to
influence other judgments of faces [24–31]. Another limitation is
that the faces we used were sampled from particular populations.
South Asian faces are different from the East Asian Korean faces
we used, and Black faces from various origins are different from
the African-American faces we used. However, since the Korean
faces were randomly selected from a college yearbook, our racial
prototypicality findings should generalize to that population.
Moreover, African-American faces, including the particular ones
in our sample, have shown socially significant effects of racial
prototypicality in previous research [1,3,4], which underscores the
value of determining what influences their perceived prototypicality. Nevertheless, replication of our findings with other samples
of faces is important for assessing their generalizability.
Finally, there were variations in the photographic qualities of
the facial images due to our use of a variety of databases in order
to secure a sufficient number of target images of each race.
However, we do not believe that these compromise our
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Skin Tone, Face Structure, Race Prototypicality
Table 4. Contribution of Skin Tone and Facial Metrics to Racial Prototypicality of White, Black, and Korean Faces.a
Caucasian Prototypicality
African Prototypicality
Asian Prototypicality
White
Black
Korean
White
Black
Korean
White
Black
Korean
b
b
b
b
b
b
b
b
b
Skin Tone DR2
.04
.20**
.34**
.06*
.13**
.30**
.00
.17**
.21**
Facial Metrics DR2
.26*
.13*
.06
.23
.15
.09
.27
.12
.12
Perceiver Race
White Faces
Black Faces
Skin Tone DR2
.02
.31**
.14**
.00
.40**
.19**
.00
.26**
.12**
Facial Metrics DR2
.51**
.20**
.27*
.32*
.19**
.17
.16
.20
.18
Korean Faces
Skin Tone DR2
.00
.02
.07**
.16**
.13**
.17**
.03
.01
.01
Facial Metrics DR2
.37**
.33**
.27**
.32**
.26*
.14*
.48**
.39**
.44**
a
Note. Facial attractiveness, babyfaceness, smile scores, and face sex were controlled in all regressions; metrics also were controlled in the regressions predicting from
skin tone, and skin tone was controlled in the regressions prediction from metrics.
*p,05;
**p,001.
doi:10.1371/journal.pone.0041193.t004
conclusions. First, we divided each facial metric by inter-pupil
distance, a standard normalization technique to control for
variations in distance from the camera [20–22]. Second, although
the different data bases made it difficult to obtain comparable
objective measures of skin tone and also could have influenced the
subjective ratings we used, there was strong inter-rater agreement
for these ratings. For our purposes, the contribution to prototypicality judgments of these reliably perceived differences in skin
tone among faces that are all the same race is more important than
any objective measure of differences in skin tone. Moreover, it is
important to note that both skin tone and prototypicality ratings
were made with reference to faces of a single race. Consequently,
between race differences in photographic qualities do not
compromise our conclusions regarding the determinants of racial
prototypicality within faces of each race, and within-race
variations in quality do not compromise our conclusions regarding
differences in determinants across perceivers of different races.
Another issue regarding the generalizability of our results is
whether they would hold true in more ecologically valid contexts.
Some affirmative evidence is provided by the fact that both
appearance ratings and facial metrics of static photographs predict
trait impressions of dynamic images of the same faces, and they do
so even when vocal cues are provided [32,33]. Moreover, racial
prototypicality judgments and other subjective impressions of
static facial images, including some used in the present study,
predict variations in actual life outcomes among the individuals
depicted, variations in photographic qualities notwithstanding
[3,4,34,35]. These findings provide reason to believe that the facial
metric predictors of prototypicality ratings in the present study
would generalize to perceived prototypicality in real life contexts.
The variations in perceived racial prototypicality that we have
documented have interesting implications for other race-related
responses, including the well-documented other-race effect (ORE),
whereby perceivers show poorer recognition of other-race than
own-race faces [36]. For example, the stronger influence of skin
tone on Black than White perceivers’ prototypicality ratings
suggests that large variations in skin tone among faces would
reduce the ORE effect more for Black perceivers than for White
perceivers. Similarly, the stronger influence of facial metrics on
White than Black perceivers’ racial prototypicality ratings suggests
PLoS ONE | www.plosone.org
that large variations in facial metrics would reduce the ORE effect
for White perceivers more than for Black perceivers. This possible
contribution of specific facial qualities to the ORE provides a
novel addition to accounts that focus on greater experience
processing own-race faces or greater motivation to do so [37].
Variations in perceived racial prototypicality also have significant implications for predicting the facial qualities that make
people vulnerable to prejudice – those who will experience racial
prototypicality biases and from whom, Consider, for example, the
evidence that U.S. judges, who are largely White, give longer
prison terms to more African-looking White or Black defendants
[3], and are more likely to give the death penalty to more Africanlooking Black defendants convicted of murdering a White victim
[4]. Our results indicate that the more African-looking White
convicts are those with darker-skin more so than those with more
African-looking facial features. Indeed, the greater importance of
skin tone than facial metrics when judging African prototypicality
of White faces held true in our study regardless of perceiver race.
In the case of Black convicts, our results suggest that those with
more African-looking features are at greater risk for harsh
punishment than those with darker skin if they are sentenced by
White perceivers, for whom facial metrics had more impact on
African prototypicality ratings. In contrast, if perceivers are Black,
then darker skin will have more impact on perceived African
prototypicality than more African-looking features. However,
there is reason to expect that Black perceivers would not respond
negatively to a more African-looking appearance, and they may
even respond positively [15,38,39]. Finally, for Korean convicts,
our results indicate that either darker skin or more African-looking
features could put them at greater risk regardless of the perceiver’s
race.
Although we have illustrated the implications of our findings for
people of different races with a more prototypically African
appearance, it would be interesting to explore the implications for
people with a more prototypically Asian appearance, particularly
given evidence that Asians are viewed as the ‘model minority’ in
the United States [40,41], as well as for people with a more
prototypically White appearance. Also, although we have
discussed implications for the judicial system, racial prototypicality
effects may be found in other domains where facial appearance
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Skin Tone, Face Structure, Race Prototypicality
has been shown to influence social outcomes, including education,
employment, and health care [42]. Knowing what objective facial
qualities influence subjective racial prototypicality assessments by
various perceivers is important for efforts to ameliorate such
biases.
Acknowledgments
The authors thank Irene Blair for sharing her images of Black male faces
with us, Judy Hall for providing assistance recruiting and running Black
participants, Ryeo-Jin Ko for collecting data in Korea, Jeong-Sook Lee and
So Young Goode for translating the experimental materials into Korean,
Aviva Androphy, Shayna Skelley, Naomi Skop, Rebecca Wienerman, and
Glenn Landauer for help finding, scanning, and standardizing facial
images and collecting data in the US, and Masako Kikuchi for
coordinating the foregoing tasks.
Supporting Information
Table S1 DR2 and Standardized Beta Weights from
Regressions Predicting Caucasian, African, and Asian
Prototypicality.
(DOC)
Author Contributions
Conceived and designed the experiments: LAZ MS. Performed the
experiments: MS PMB HKL. Analyzed the data: MS SZ PMB. Wrote the
paper: LAZ MS.
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